Open-source controller for low-cost and high-speed atomic force microscopy imaging of skin corneocyte nanotextures

Graphical abstract


a b s t r a c t
High-speed atomic force microscopes (HS-AFMs) with high temporal resolution enable dynamic phenomena to be visualized at nanoscale resolution. However, HS-AFMs are more complex and costlier than conventional AFMs, and particulars of an open-source HS-AFM controller have not been published before. These high entry barriers hinder the popularization of HS-AFMs in both academic and industrial applications. In addition, HS-AFMs generally have a small imaging area that limits the fields of implementation. This study presents an open-source controller that enables a low-cost simplified AFM to achieve a maximum tip-sample velocity of 5,093 lm/s (9.3 s/frame, 512 Â 512 pixels), which is nearly 100 times higher than that of the original controller. Moreover, the proposed controller doubles the imaging area to 46.3 Â 46.3 lm 2 compared to that of the original system. The low-cost HS-AFM can successfully assess the severity of atopic dermatitis (AD) by measuring the nanotexture of human skin corneocytes in constant height DC mode. The open-source controller-based HS-AFM system costs less than $4,000, which provides resource-limited research institutes with affordable access to high-throughput nanoscale imaging to further expand the HS-AFM research community. The controller connects to a commercial simplified AFM system (Strømlingo DIY AFM, Strømlinet Nano), which includes an Arduino-based controller and AFM head on a supporting structure. The open-source controller generates fast-axis (FastX) and slow-axis (SlowY) scanning signals through two analog outputs, and one analog input receives a focus error signal (FES) [45] generated by the simplified AFM controller. The scan data are transferred from the HS-AFM controller to a personal computer (PC) via the first-in-first-out (FIFO) queuing mechanism to display the real-time scanning image.

Open-source controller
The embedded device of the controller is based on a field-programmable gate array (FPGA) real-time microcontroller unit, which enables high-speed scanning control and parallel function execution. Moreover, the FPGA can be programmed using the LabVIEW software (National Instruments) with a user-friendly graphical interface. In addition, the open-source LabVIEW code of the controller provides a foundation on which users are able to build their own functions. The embedded device has a mini system port (MSP) terminal that interfaces the digital-to-analog converters (DACs) and analog-to-digital converters (ADCs). Two of these DACs (AO0 and AO1), with 12 bits resolution and 345 kS/s update rates, are used to output FastX and SlowY driving signals, respectively. The FES is connected to one ADC, with a resolution of 12 bits and a sampling rate of 500 kS/s.
To avoid unwanted scanner oscillation excited by conventional zig-zag raster scanning, a different approach was followed to implement the open-source HS-AFM. The fast-axis is driven by a sinusoidal scanning signal to eliminate high-frequency components when the scanning direction changes. The sinusoidal signal is generated by the open-source controller using a lookup table for high-speed scanning. A drawback of using the sinusoidal trajectory is that the velocity of the sinusoidal scanning motion is not constant, which can cause image distortion while using a constant sampling rate. To solve this problem, the HS-AFM controller captures the FES using a non-constant sampling rate, as illustrated in Fig. 2. The FES is acquired when the sinusoidal scanning signal arrives at defined voltage levels with a constant voltage interval DV. The scanning signal is proportional to the scanner displacement if we assume the time delay between the driving signal and the movement to be negligible. Therefore, an FES with a constant displacement interval can be obtained using a time-varying sampling rate.

Open-Source buffer circuit
The open-source buffer circuit is built to amplify the FastX and SlowY scanning signals to overcome the output current limitation (2 mA) of the embedded device. The buffer circuit consists of an operational amplifier (AD8397ARZ, Analog   Devices), which supplies the FastX and SlowY driving signals with a maximum output current and voltage of 310 mA and ±12 V, respectively. The amplified driving signals are directly connected to the scanner of the simplified AFM for highspeed scanning, as shown in Fig. 1. The buffer circuit has a connector that directly plugs into a mini system port of the embedded device.

Simplified AFM
The simplified AFM consists of a controller, an AFM head, a supporting structure that contains an AFM base, and an antivibration device. The simplified AFM controller is connected to the AFM head via a flat cable. The AFM head utilizes a DVD optical pick-up unit (OPU) [46][47][48] to monitor the cantilever deflection [49][50][51] of the AFM probe [52][53][54]. The AFM base consists of a piezoelectric buzzer-based scanner [55,56] to scan a sample in the x-and y-directions. The anti-vibration device is a cage-like flexible structure that supports the AFM base and isolates the external vibration during measurement.  The simplified AFM controller has two knobs, VCM_Z and VCM_X, to control the movement in the z-and x-directions of the voice coil motor (VCM) on the OPU. The VCM actuates an objective lens of the OPU to focus a laser on the AFM probe. The simplified AFM controller calculates signals from the OPU [57] and provides the FES that is proportional to the AFM probe deflection [58]. The FES detection range can be adjusted to 1 lm, 2 lm, or 4 lm using dip switches on the controller, and the corresponding resolutions are 0.2 nm, 0.48 nm, and 0.97 nm, respectively. The simplified AFM has a maximum scan speed of 0.6 lines/s (see the video ''Simplified AFM with the original controller for 0.6 lines per second imaging.mp4 00 ) with a limited image resolution of 256 Â 256 pixels and a small scan range of 23 Â 23 lm 2 . The controller provides signal input pins for external scanning control. However, buffer circuits inside the controller cannot provide sufficient current output, and the maximum scanning speed is limited to 13.8 lm/s. Thus, the proposed approach is to bypass the original controller and connect the scanning signals in the x-and y-directions to the AFM scanner directly.
In summary, the presented open-source controller provides the following benefits: Enables a low-cost simplified system for HS-AFM imaging.
Eliminates unwanted scanner oscillation with sinusoidal scanning motion.

Operation instructions
The user interface was developed in LabVIEW and executed on a PC. The following procedure should be followed to operate the open-source controller-based HS-AFM system.
1. Install the executable file (AFM.exe) on the PC. 2. Open the software installed in the PC directory (C drive is the default installation directory). Doing so opens the control and imaging windows, as shown in Fig. 4. The FES appears in the control window. 3. Install the AFM probe on the AFM head. The cantilever of the AFM probe should be positioned in front of the objective lens of the OPU [59]. 4. Adjust the VCM_Z and VCM_X knobs on the simplified AFM controller to adjust the laser focus on the cantilever. Turning the VCM_Z knob back and forth produces an S-shaped curve in the FES of the control window. Adjust the position of VCM_Z such that the FES is in the linear range of the S-curve. 5. A video in the file repository entitled ''Focus laser on an AFM probe and start measurement.mp4 00 demonstrates the laser alignment process in detail. 6. Load a sample on the AFM sample stage and mount the AFM head on the AFM base such that the three precision screws are in contact with the AFM base. Ensure sufficient space between the AFM probe and sample before mounting the AFM head on the AFM base. 7. To test the sensitivity of the system, gently tap on one of the screws; the variation in the FES is displayed in the control window. 8. Carefully approach the AFM probe by turning the three precision screws equally to avoid tilting the AFM head. Because the approaching mechanism is a manual process, setpoint and feedback control are unnecessary. While approaching the AFM probe, the oscillation of the FES can be seen in the control window; the amplitude becomes constant once the tip is in contact with the sample. When the change in the FES amplitude is more than 20 %, stop the approaching process. 9. Define the scanning parameters (scan rate, range, type) and press the start scan button in the control window to start scanning. The image appears in the imaging window. 10. The image contrast can be adjusted by using the mouse and drawing a rectangle on the trace or retrace image. 11. A video in the file repository entitled ''Operation process of the open-source controller-based HS-AFM.mp4 00 demonstrates the software operation in detail.

Calibration and limitation
A piece (ca. 1 Â 1 cm 2 ) of a data track layer (from a rewritable DVD) was used as a low-cost sample to calibrate the HS-AFM scanner. The DVD data tracks have a fixed period of 740 nm and a defined depth of 160 nm [60]. The scanning area and Z sensitivity of the FES can be calibrated by measuring the DVD data tracks. DC mode AFM probes with a spring constant of 0.03 N/m (aluminum coating on the detector side, Mikromasch, Germany) were used for nanoscale imaging. The HS-AFM calibration was performed in constant-height DC mode in an ambient environment. The HS-AFM image was subjected to raw data processing with free data analysis software (Gwyddion [61]). A video in the file repository entitled ''Simplified AFM scanner calibration process.mp4 00 shows the calibration process in detail.
The performances of the simplified AFM and open-source HS-AFM controllers were compared experimentally. Fig. 5a and 5b show the images of the DVD tracks acquired by the two controllers with the same AFM head and supporting structure. Three main parameters are responsible for limiting the maximum imaging speed of the HS-AFM. First, the DACs of the embedded device can provide a maximum scanning rate of 336 lines/s (345 kS/s update rate divided by trace/retrace direction in a total of 1024 points). Second, the current output from the open-source buffer circuit is 310 mA, which can drive the scanner capacitive load (single axis: 72 nF) for scanning at more than 1,000 lines/s. Lastly, the buzzer scanner has a resonance frequency of 55 Hz, which is a bottleneck in terms of increasing the scanning speed in this study. In other words, we expect the imaging speed of the HS-AFM based on the open-source controller to increase by increasing the resonance frequency of the scanner.

Nanotexture based skin barrier function assessment
Clinical studies confirmed that the density of circular nanotextures (typical height: 273 nm, width: 305 nm) on human corneocyte surfaces is inversely associated with natural moisturizing factor (NMF) concentrations [62]. Moreover, an image recognition algorithm based on machine learning was developed to quantify the circular nanotexture density within 20x20 lm 2 areas into a dermal texture index (DTI) [63]. The DTI could be an objective score to assess the severity of atopic dermatitis (AD) [64]. The DTI score ranges from 0 to 800. Healthy skin has a score of less than 100, and a score of 200 is the threshold for AD clinical symptoms. A score over 400 indicates that a severe case of AD is expected. The HS-AFM based on the open-source controller is capable of assessing skin barrier function by imaging nanotextures on human skin corneocyte surfaces. Because AFM probes that operate in DC mode have a low spring constant, the constant height DC scanning mode can effectively image the nanotextures on skin corneocytes. Fig. 6a shows a 20 Â 20 lm 2 topography image of a skin corneocyte from a healthy donor. An evaluation method based on machine learning, DERMATACT (Serend-Ip GmbH, Münster, Germany), was used to analyze this image, and 135 circular nanotextures (indicated in green) were recognized, as shown in Fig. 6b. The total area and the average height of the circular nanotextures are 4.22 Â 10 7 ± 2.9 Â 10 6 nm 2 and 297 ± 20 nm, respectively.
The HS-AFM based on the open-source controller was subsequently used to examine healthy control and AD lesional skin corneocytes from donors. The healthy control yields a low DTI score of 65, as shown in Fig. 7a. The AD lesional skin (Fig. 7b) has many circular nanotextures and the DTI score is 332. The results show that the proposed open-source HS-AFM can successfully differentiate healthy and AD skins.

Conclusion
The open-source controller transforms the existing infrastructure, a low-cost simplified AFM, into a high-speed AFM (HS-AFM) with a tip-sample velocity of 5,093 lm/s. Moreover, the HS-AFM acquired one skin nanotexture image in 9.3 s with a constant height DC mode. The acquired skin nanotexture images satisfy the DTI calculation requirements, scan area: 20 Â 20 lm 2 and image pixel: 512 Â 512 pixels, for quantified AD severity assessment. The nanotexture images, when combined with DTI scores, can be used to differentiate between healthy and AD skins. The open-source controller fulfills the need for samples with a large area and flat morphology (such as skin corneocytes with a height difference <3 lm) with constantheight DC mode HS-AFM measurement. We believe that in addition to working on simplified AFMs, the open-source controller can upgrade old AFMs to have high-speed DC mode measurements, thereby further expanding the HS-AFM research community.

Potential modifications
To optimize the performance of the open-source buffer circuit, we added 1 X resistors to dampen the resonance frequency of the power supply filter. Buffer capacitors were added to stabilize the operational amplifier. The modified opensource buffer circuit design files can be found in the file repository entitled ''buffer circuit Ver. 2.0 design". In the buffer circuit Ver. 2.0 design, FastX and SlowY are assigned the labels FASTXOUT and SLOWYOUT, respectively.

Ethics statement
Informed and written consents were obtained from all participants, and the study was conducted in accordance with the Declaration of Helsinki principles. The protocol was approved by the regional ethics committee (H-2207232) and the Danish Data Protection Agency.

Declaration of Competing Interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The author Dr. En-Te Hwu was a technical consultant of the simplified AFM company (Strømlinet Nano). This does not affect his adherence to scientific standards.